Journal articles: 'Fractional Bayes factor'

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Conigliani, Caterina, and Anthony O'hagan. "Sensitivity of the fractional Bayes factor to prior distributions." Canadian Journal of Statistics 28, no. 2 (June 2000): 343–52. http://dx.doi.org/10.2307/3315983.

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De Santis, Fulvio, and Fulvio Spezzaferri. "Consistent fractional Bayes factor for nested normal linear models." Journal of Statistical Planning and Inference 97, no. 2 (September 2001): 305–21. http://dx.doi.org/10.1016/s0378-3758(00)00240-8.

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Dittrich, Dino, Roger Th A. J. Leenders, and Joris Mulder. "Network Autocorrelation Modeling: A Bayes Factor Approach for Testing (Multiple) Precise and Interval Hypotheses." Sociological Methods & Research 48, no. 3 (October 12, 2017): 642–76. http://dx.doi.org/10.1177/0049124117729712.

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Currently available (classical) testing procedures for the network autocorrelation can only be used for falsifying a precise null hypothesis of no network effect. Classical methods can be neither used for quantifying evidence for the null nor for testing multiple hypotheses simultaneously. This article presents flexible Bayes factor testing procedures that do not have these limitations. We propose Bayes factors based on an empirical and a uniform prior for the network effect, respectively, first. Next, we develop a fractional Bayes factor where a default prior is automatically constructed. Simulation results suggest that the first two Bayes factors show superior performance and are the Bayes factors we recommend. We apply the recommended Bayes factors to three data sets from the literature and compare the results to those coming from classical analyses using p values. R code for efficient computation of the Bayes factors is provided.

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Ariza-Hernandez, Francisco J., Jorge Sanchez-Ortiz, Martin P. Arciga-Alejandre, and Luis X. Vivas-Cruz. "Bayesian Analysis for a Fractional Population Growth Model." Journal of Applied Mathematics 2017 (2017): 1–9. http://dx.doi.org/10.1155/2017/9654506.

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We implement the Bayesian statistical inversion theory to obtain the solution for an inverse problem of growth data, using a fractional population growth model. We estimate the parameters in the model and we make a comparison between this model and an exponential one, based on an approximation of Bayes factor. A simulation study is carried out to show the performance of the estimators and the Bayes factor. Finally, we present a real data example to illustrate the effectiveness of the method proposed here and the pertinence of using a fractional model.

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de Santis, Fulvio, and Fulvio Spezzaferri. "Methods for Default and Robust Bayesian Model Comparison: The Fractional Bayes Factor Approach." International Statistical Review / Revue Internationale de Statistique 67, no. 3 (December 1999): 267. http://dx.doi.org/10.2307/1403706.

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Santis, Fulvio, and Fulvio Spezzaferri. "Methods for Default and Robust Bayesian Model Comparison: the Fractional Bayes Factor Approach." International Statistical Review 67, no. 3 (December 1999): 267–86. http://dx.doi.org/10.1111/j.1751-5823.1999.tb00449.x.

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Mashayekhi, Somayeh, and Peter Beerli. "Fractional coalescent." Proceedings of the National Academy of Sciences 116, no. 13 (March 13, 2019): 6244–49. http://dx.doi.org/10.1073/pnas.1810239116.

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An approach to the coalescent, the fractional coalescent (f-coalescent), is introduced. The derivation is based on the discrete-time Cannings population model in which the variance of the number of offspring depends on the parameter α. This additional parameter α affects the variability of the patterns of the waiting times; values ofα<1lead to an increase of short time intervals, but occasionally allow for very long time intervals. Whenα=1, the f-coalescent and the Kingman’s n-coalescent are equivalent. The distribution of the time to the most recent common ancestor and the probability that n genes descend from m ancestral genes in a time interval of length T for the f-coalescent are derived. The f-coalescent has been implemented in the population genetic model inference software Migrate. Simulation studies suggest that it is possible to accurately estimate α values from data that were generated with known α values and that the f-coalescent can detect potential environmental heterogeneity within a population. Bayes factor comparisons of simulated data withα<1and real data (H1N1 influenza and malaria parasites) showed an improved model fit of the f-coalescent over the n-coalescent. The development of the f-coalescent and its inclusion into the inference program Migratefacilitates testing for deviations from the n-coalescent.

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Kaiser, Andrew R., Nihan S. Pol, Maura A. McLaughlin, Siyuan Chen, Jeffrey S. Hazboun, Luke Zoltan Kelley, Joseph Simon, Stephen R. Taylor, Sarah J. Vigeland, and Caitlin A. Witt. "Disentangling Multiple Stochastic Gravitational Wave Background Sources in PTA Data Sets." Astrophysical Journal 938, no. 2 (October 1, 2022): 115. http://dx.doi.org/10.3847/1538-4357/ac86cc.

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Abstract With strong evidence of a common-spectrum stochastic process in the most recent data sets from the NANOGrav Collaboration, the European Pulsar Timing Array (PTA), Parkes PTA, and the International PTA, it is crucial to assess the effects of the several astrophysical and cosmological sources that could contribute to the stochastic gravitational wave background (GWB). Using the same data set creation and injection techniques as in Pol et al., we assess the separability of multiple GWBs by creating single and multiple GWB source data sets. We search for these injected sources using Bayesian PTA analysis techniques to assess recovery and separability of multiple astrophysical and cosmological backgrounds. For a GWB due to supermassive black hole binaries and an underlying weaker background due to primordial gravitational waves with a GW energy-density ratio of ΩPGW/ΩSMBHB = 0.5, the Bayes’ factor for a second process exceeds unity at 17 yr, and increases with additional data. At 20 yr of data, we are able to constrain the spectral index and amplitude of the weaker GWB at this density ratio to a fractional uncertainty of 64% and 110%, respectively, using current PTA methods and techniques. Using these methods and findings, we outline a basic protocol to search for multiple backgrounds in future PTA data sets.

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O'Hagan, Anthony. "Fractional Bayes Factors for Model Comparison." Journal of the Royal Statistical Society: Series B (Methodological) 57, no. 1 (January 1995): 99–118. http://dx.doi.org/10.1111/j.2517-6161.1995.tb02017.x.

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O’Hagan, A. "Properties of intrinsic and fractional Bayes factors." Test 6, no. 1 (June 1997): 101–18. http://dx.doi.org/10.1007/bf02564428.

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Vijayaragunathan, R., and M. R. Srinivasan. "Comparisons of Bayes factors for 𝟐𝟒 full, fractional, and reduced factorial designs." International Journal of ADVANCED AND APPLIED SCIENCES 9, no. 9 (September 2022): 158–67. http://dx.doi.org/10.21833/ijaas.2022.09.020.

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The effect of factors in full and fractional factorial designs is being studied ubiquitously in all fields of science and engineering. At times, researchers would want to gather additional information than the fractional factorial design provided, there is no restriction to conducting more experimental runs. In this study, we propose a reduced fractional factorial design consisting of all significant factors. This paper illustrates the effectiveness of factors through real data application and simulation by comparing the full factorial, reduced factorial, and fractional factorial designs. The actual weightage of the main/interaction effects in these three designs was found by identifying and quantifying the Bayes factors through the simulation datasets. It is observed that the reduced factorial design produces better results when there are no constraints to select or add factors to the model.

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Vijayaragunathan, R., and M. R. Srinivasan. "Comparisons of Bayes factors for 𝟐𝟒 full, fractional, and reduced factorial designs." International Journal of ADVANCED AND APPLIED SCIENCES 9, no. 9 (September 2022): 158–67. http://dx.doi.org/10.21833/ijaas.2022.09.020.

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The effect of factors in full and fractional factorial designs is being studied ubiquitously in all fields of science and engineering. At times, researchers would want to gather additional information than the fractional factorial design provided, there is no restriction to conducting more experimental runs. In this study, we propose a reduced fractional factorial design consisting of all significant factors. This paper illustrates the effectiveness of factors through real data application and simulation by comparing the full factorial, reduced factorial, and fractional factorial designs. The actual weightage of the main/interaction effects in these three designs was found by identifying and quantifying the Bayes factors through the simulation datasets. It is observed that the reduced factorial design produces better results when there are no constraints to select or add factors to the model.

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Gu, Xin, Joris Mulder, and Herbert Hoijtink. "Approximated adjusted fractional Bayes factors: A general method for testing informative hypotheses." British Journal of Mathematical and Statistical Psychology 71, no. 2 (August 31, 2017): 229–61. http://dx.doi.org/10.1111/bmsp.12110.

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Yang, Xihua. "Deriving RUSLE cover factor from time-series fractional vegetation cover for hillslope erosion modelling in New South Wales." Soil Research 52, no. 3 (2014): 253. http://dx.doi.org/10.1071/sr13297.

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Soil loss due to water erosion, in particular hillslope erosion, can be estimated using predictive models such as the Revised Universal Soil Loss Equation (RUSLE). One of the important and dynamic elements in the RUSLE model is the cover and management factor (C-factor), which represents effects of vegetation canopy and ground cover in reducing soil loss. This study explores the potential for using fractional vegetation cover, rather than traditional green vegetation indices (e.g. NDVI), to estimate C-factor and consequently hillslope erosion hazard across New South Wales (NSW), Australia. Values of the C-factor were estimated from the emerging time-series fractional cover products derived from Moderate Resolution Imaging Spectroradiometer (MODIS). Time-series C-factor and hillslope erosion maps were produced for NSW on monthly and annual bases for a 13-year period from 2000 to 2012 using automated scripts in a geographic information system. The estimated C-factor time-series values were compared with previous study and field measurements in NSW revealing good consistency in both spatial and temporal contexts. Using these time-series maps, the relationship was analysed between ground cover and hillslope erosion and their temporal variation across NSW. Outcomes from this time-series study are being used to assess hillslope erosion hazard, sediment and water quality (particularly after severe bushfires) across NSW at local, catchment and regional scales.

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Ondráček, Jan, Josef Janků, Jiří Novotný, Luděk Vodička, László Csordás, and Bohumil Kratochvíl. "The Bayer-Villiger oxidation of diamantanone and the structure of 11-oxo-10-oxapentacyclo[7,4,1,14,13,02,7,06,12]-pentadecane." Collection of Czechoslovak Chemical Communications 54, no. 12 (1989): 3260–66. http://dx.doi.org/10.1135/cccc19893260.

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The studied substance was prepared by the Bayer-Villiger oxidation of diamantanone and identified by 1H and 13C NMR spectroscopy. The structure of the compound was solved by direct methods and refined to the value R = 0.052 for 845 observed reflections (I > 1.96σ(I)). The substance crystallizes in the orthorhombic space group Pnnm; a = 23.595(4), b = 10.284(2), c = 6.676(1) Å. The unit cell of the crystal structure of 11-oxo-10-oxapentacyclo[7,4,1,14,13,02,7,06,12]pentadecane contains four ordered and two disordered molecules. The disordered molecule is described by averaging the image of the ordered molecule and its inverse image. Thus, the unit cell contains 6 formula units (part of the atoms have fractional occupation factors) even though the multiplicity of the general position in the Pnnm group is 8.

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Martínez, Carlos Alberto, Kshitij Khare, Arunava Banerjee, and Mauricio A. Elzo. "Joint genome-wide prediction in several populations accounting for randomness of genotypes: A hierarchical Bayes approach. II: Multivariate spike and slab priors for marker effects and derivation of approximate Bayes and fractional Bayes factors for the complete family of models." Journal of Theoretical Biology 417 (March 2017): 131–41. http://dx.doi.org/10.1016/j.jtbi.2016.12.022.

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Mohapatra, Sushmita, Kei-Long Cheung, Mickaël Hiligsmann, and Nana Anokye. "Most Important Factors for Deciding Rehabilitation Provision for Severe Stroke Survivors Post Hospital Discharge: A Study Protocol for a Best–Worst Scaling Experiment." Methods and Protocols 4, no. 2 (May 6, 2021): 27. http://dx.doi.org/10.3390/mps4020027.

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Efficient decision-making is crucial to ensure adequate rehabilitation with optimal use of healthcare resources. Establishing the factors associated with making decisions concerning rehabilitation provision is important to guide clinical staff towards person-centred decisions for rehabilitation after severe stroke. In this study we conduct a best–worst scaling (BWS) experiment to identify the most important factors and their relative weight of importance for deciding the type of ongoing rehabilitation services a person with severe stroke might receive post hospital discharge. Fractional, efficient designs are applied regarding the survey design. Key multidisciplinary staff regularly involved in making decisions for rehabilitation in a stroke unit will be recruited to participate in an online BWS survey. Hierarchical Bayes estimation will be used as the main analysis method, with the best–worst count analysis as a secondary analysis. The survey is currently being piloted prior to commencing the process of data collection. Results are expected by the end of September 2021. The research will add to the current literature on clinical decision-making in stroke rehabilitation. Findings will quantify the preferences of factors among key multi-disciplinary clinicians working in stroke units in the UK, involved in decision-making concerning rehabilitation after stroke.

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Garzón, Julián, Iñigo Molina, Jesús Velasco, and Andrés Calabia. "A Remote Sensing Approach for Surface Urban Heat Island Modeling in a Tropical Colombian City Using Regression Analysis and Machine Learning Algorithms." Remote Sensing 13, no. 21 (October 22, 2021): 4256. http://dx.doi.org/10.3390/rs13214256.

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The Surface Urban Heat Islands (SUHI) phenomenon has adverse environmental consequences on human activities, biophysical and ecological systems. In this study, Land Surface Temperature (LST) from Landsat and Sentinel-2 satellites is used to investigate the contribution of potential factors that generate the SUHI phenomenon. We employ Principal Component Analysis (PCA) and Multiple Linear Regression (MLR) techniques to model the main temporal and spatial SUHI patterns of Cartago, Colombia, for the period 2001–2020. We test and evaluate the performance of three different emissivity models to retrieve LST. The fractional vegetation cover model using Sentinel-2 data provides the best results with R2 = 0.78, while the ASTER Global Emissivity Dataset v3 and the land surface emissivity model provide R2 = 0.27 and R2 = 0.26, respectively. Our SUHI model reveals that the factors with the highest impact are the Normalized Difference Water Index (NDWI) and the Normalized Difference Build-up Index (NDBI). Furthermore, we incorporate a weighted Naïve Bayes Machine Learning (NBML) algorithm to identify areas prone to extreme temperatures that can be used to define and apply normative actions to mitigate the negative consequences of SUHI. Our NBML approach demonstrates the suitability of the new SUHI model with uncertainty within 95%, against the 88% given by the Support Vector Machine (SVM) approach.

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Lazzara, Matthew J., and William M. Deen. "Model of albumin reabsorption in the proximal tubule." American Journal of Physiology-Renal Physiology 292, no. 1 (January 2007): F430—F439. http://dx.doi.org/10.1152/ajprenal.00010.2006.

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Normally, the small amount of albumin which passes through the glomerular capillary wall is almost completely reabsorbed in the proximal tubule, via an endocytic mechanism, but the reabsorptive process can be overwhelmed if the filtered load of albumin is too large. To examine the factors that control the fractional reabsorption of albumin ( f), we developed a mathematical model which assumes saturable endocytosis kinetics with a maximum reabsorptive capacity, V max, and which includes the effects of flow and diffusion in the lumen. Limitations in albumin transport from the bulk tubule fluid to the endocytic sites at the bases of the microvilli had only a modest (8%) effect on the value of V max needed to fit micropuncture data on tubule albumin concentrations in rats. For moderate changes in filtered load, there was much greater sensitivity of f to SNGFR than to the albumin concentration of the filtrate ( C0). A 50% increase in SNGFR was predicted to cause four- to fivefold increases in albumin excretion in rats or humans. For large increases in C0, as might result from defects in glomerular sieving, there was a threshold at which the reabsorptive process became saturated and f fell sharply. That threshold corresponded to sieving coefficients of 10−3 to 10−2, the higher values occurring at reduced SNGFR. The predictions of the present model contrast with those of one proposed recently by Smithies ( 32 ), which does not include the effects of tubule flow rate.

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Picker, Nils, Alexander T. Cohen, Anthony Maraveyas, Jan Beyer-Westendorf, Agnes Yuet Ying Lee, Lorenzo G. Mantovani, Yoriko De Sanctis, et al. "Patient Preferences Regarding Anticoagulation Therapy in Patients with Cancer Having a VTE Event - a Discrete Choice Experiment in the Cosimo Study." Blood 134, Supplement_1 (November 13, 2019): 2159. http://dx.doi.org/10.1182/blood-2019-128095.

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Introduction: Current guidelines recommend low-molecular-weight heparins (LMWH) over Vitamin K Antagonists (VKA) or Non-Vitamin K Antagonist Oral Anticoagulants (NOAC) for the treatment of cancer-associated venous thromboembolism (CAT), but also highlight that ultimately the choice of anticoagulant depends on patient-specific factors such as patient preferences, which is important for the acceptance of the treatment and, thus, for adherence and persistence. So far, little is known about the specific preferences of patients with CAT with respect to anticoagulation therapy. More specifically, the impact of dosing regimen, convenience and costs on patient preferences in CAT is poorly understood. Therefore, the objective of this discrete choice experiment (DCE) was to elucidate patient preferences regarding anticoagulation convenience attributes. Methods: Adult patients with active cancer who experienced a CAT event and for whom the decision was made to start a treatment with rivaroxaban after being treated with the standard of care anticoagulation (LMWH/VKA) for at least four weeks were included in a multinational, observational, single-arm study (COSIMO). As part of this study, a DCE was presented to the participants, who were asked to decide between complete hypothetical treatment options based on a combination of different attributes, regardless of efficacy or safety. The following attributes were preselected in a face-to-face discussion with three focus patients and in-depth interviews with four additional patients: route of administration (injection / tablet),frequency of intake (once / twice daily),need of regular controls of the International Normalized Ratio (INR) at least every 3-4 weeks (yes/no),interactions with food/alcohol (yes/no). Additionally, distance to treating physician (1 km vs. 20 km) was included as neutral comparator to express patients' overall utility in terms of a comprehensible unit. The relative importance of treatment attributes in terms of distances were calculated based on ratios between the utility estimates for each attribute. A fractional factorial design was generated resulting in nine hypothetical choice sets, supplemented by a test choice set to assess the consistency of a patient's responses. DCE data was collected by semi-structured telephone interviews, performed between week 4 and week 12 after enrollment of patients in the study and start of rivaroxaban. For each patient participating in the DCE interview, a written informed consent was obtained. Patient preferences were analyzed based on a conditional logit regression model. Results: Overall, 163 patients were included (Europe: 119; Canada: 41; Australia: 3), mean age 63.7 years, 49.1% were females and diagnosed with cancer for on average 22.4 months. Most patients in the COSIMO study changed to rivaroxaban from LMWH (> 95.0 %). The median time from diagnosis of index CAT event to conduct of DCE was 150 days (IQR 88-229). Patients strongly preferred oral administration compared to self-injections and drugs that can be taken irrespective of type of food or alcohol consumption (Figure 1). Furthermore, patients indicated slight preference for a shorter distance to the treating physician and a once daily dosing regimen compared to a twice-daily intake. The attribute "INR controls" showed no significant impact on the treatment decision. In order of patients' preference for their choice of treatment, the route of administration was by far the most important attribute for a patient's choice (73.8% of the overall decision), followed by food interactions (11.8%), the distance to treating physician (7.2%) and the intake frequency (6.5%). Accordingly, the expected utility of patients receiving an oral anticoagulation can be expressed as willingness to travel an additional distance of 192 km to the treating physician in order to avoid an injection. Conclusions Treatment related decision-making of patients with CAT, assuming equal effectiveness and safety of treatments, is predominantly driven by "route of administration", indicating a strong preference for oral intake. Disclosures Picker: Ingress-Health: Employment. Cohen:Bristol-Myers Squibb: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; ACI Clinical: Consultancy; GLG: Consultancy; GlaxoSmithKline: Consultancy, Speakers Bureau; Daiichi-Sankyo: Consultancy, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; CSL Behring: Consultancy; Boston Scientific: Consultancy; AbbVie: Consultancy; Boehringer-Ingelheim: Consultancy, Speakers Bureau; Bayer: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Aspen: Consultancy, Speakers Bureau; Guidepoint Global: Consultancy; Johnson and Johnson: Consultancy, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Leo Pharma: Consultancy; Medscape: Consultancy, Speakers Bureau; McKinsey: Consultancy; Navigant: Consultancy; ONO: Consultancy, Membership on an entity's Board of Directors or advisory committees; Sanofi: Consultancy, Membership on an entity's Board of Directors or advisory committees; Pfizer: Consultancy, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Portola: Consultancy, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Takeda: Consultancy; Temasek Capital: Consultancy; TRN: Consultancy; UK Government Health Select Committee: Other: advised the UK Government Health Select Committee, the all-party working group on thrombosis, the Department of Health, and the NHS, on the prevention of VTE; Lifeblood: Other: advisor to Lifeblood: the thrombosis charity and is the founder of the European educational charity the Coalition to Prevent Venous Thromboembolism. Maraveyas:Bayer AG: Honoraria, Research Funding; Bristol-Myers Squibb: Honoraria; Pfizer: Honoraria. Beyer-Westendorf:Pfizer: Honoraria, Research Funding; Bayer HealthCare: Honoraria, Research Funding; Boehringer Ingelheim: Honoraria, Research Funding; Daiichi Sankyo: Honoraria, Research Funding. Lee:Bristol-Myers Squibb: Consultancy, Honoraria, Research Funding; Bayer: Consultancy, Honoraria; LEO Pharma: Consultancy, Honoraria; Pfizer: Consultancy, Honoraria. Mantovani:Fondazione Charta: Consultancy; Bayer AG: Honoraria; Boehringer Ingelheim: Honoraria, Research Funding; Pfizer: Honoraria; Daiichi Sankyo: Research Funding. De Sanctis:Bayer US LLC: Employment, Equity Ownership. Abdelgawwad:Bayer AG: Employment. Fatoba:Bayer AG: Employment. Bach:Bayer AG: Employment. Wilke:Astra Zeneca: Consultancy, Honoraria; Abbvie: Consultancy, Honoraria; Novo Nordisk: Consultancy, Honoraria; Pharmerit: Consultancy, Honoraria; Bayer AG: Consultancy, Honoraria; LEO Pharma: Consultancy, Honoraria; GlaxoSmithKline: Consultancy, Honoraria; Merck: Consultancy, Honoraria; Boehringer Ingelheim: Consultancy, Honoraria.

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Fu, Qianrao, Mirjam Moerbeek, and Herbert Hoijtink. "Sample size determination for Bayesian ANOVAs with informative hypotheses." Frontiers in Psychology 13 (November 22, 2022). http://dx.doi.org/10.3389/fpsyg.2022.947768.

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Researchers can express their expectations with respect to the group means in an ANOVA model through equality and order constrained hypotheses. This paper introduces the R package SSDbain, which can be used to calculate the sample size required to evaluate (informative) hypotheses using the Approximate Adjusted Fractional Bayes Factor (AAFBF) for one-way ANOVA models as implemented in the R package bain. The sample size is determined such that the probability that the Bayes factor is larger than a threshold value is at least η when either of the hypotheses under consideration is true. The Bayesian ANOVA, Bayesian Welch's ANOVA, and Bayesian robust ANOVA are available. Using the R package SSDbain and/or the tables provided in this paper, researchers in the social and behavioral sciences can easily plan the sample size if they intend to use a Bayesian ANOVA.

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Fu, Qianrao, Herbert Hoijtink, and Mirjam Moerbeek. "Sample-size determination for the Bayesian t test and Welch’s test using the approximate adjusted fractional Bayes factor." Behavior Research Methods, July 6, 2020. http://dx.doi.org/10.3758/s13428-020-01408-1.

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Cao, Xuan, Lili Ding, and Tesfaye B. Mersha. "Joint variable selection and network modeling for detecting eQTLs." Statistical Applications in Genetics and Molecular Biology 19, no. 1 (February 20, 2020). http://dx.doi.org/10.1515/sagmb-2019-0032.

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AbstractIn this study, we conduct a comparison of three most recent statistical methods for joint variable selection and covariance estimation with application of detecting expression quantitative trait loci (eQTL) and gene network estimation, and introduce a new hierarchical Bayesian method to be included in the comparison. Unlike the traditional univariate regression approach in eQTL, all four methods correlate phenotypes and genotypes by multivariate regression models that incorporate the dependence information among phenotypes, and use Bayesian multiplicity adjustment to avoid multiple testing burdens raised by traditional multiple testing correction methods. We presented the performance of three methods (MSSL – Multivariate Spike and Slab Lasso, SSUR – Sparse Seemingly Unrelated Bayesian Regression, and OBFBF – Objective Bayes Fractional Bayes Factor), along with the proposed, JDAG (Joint estimation via a Gaussian Directed Acyclic Graph model) method through simulation experiments, and publicly available HapMap real data, taking asthma as an example. Compared with existing methods, JDAG identified networks with higher sensitivity and specificity under row-wise sparse settings. JDAG requires less execution in small-to-moderate dimensions, but is not currently applicable to high dimensional data. The eQTL analysis in asthma data showed a number of known gene regulations such as STARD3, IKZF3 and PGAP3, all reported in asthma studies. The code of the proposed method is freely available at GitHub (https://github.com/xuan-cao/Joint-estimation-for-eQTL).

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Plavén-Sigray, Pontus, Pauliina Ikonen Victorsson, Alexander Santillo, Granville J. Matheson, Maria Lee, Karin Collste, Helena Fatouros-Bergman, et al. "Thalamic dopamine D2-receptor availability in schizophrenia: a study on antipsychotic-naive patients with first-episode psychosis and a meta-analysis." Molecular Psychiatry, November 10, 2021. http://dx.doi.org/10.1038/s41380-021-01349-x.

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AbstractPharmacological and genetic evidence support a role for an involvement of the dopamine D2-receptor (D2-R) in the pathophysiology of schizophrenia. Previous molecular imaging studies have suggested lower levels of D2-R in thalamus, but results are inconclusive. The objective of the present study was to use improved methodology to compare D2-R density in whole thalamus and thalamic subregions between first-episode psychosis patients and healthy controls. Differences in thalamocortical connectivity was explored based on the D2-R results. 19 antipsychotic-naive first-episode psychosis patients and 19 age- and sex-matched healthy controls were examined using high-resolution Positron Emission Tomography (PET) and the high-affinity D2-R radioligand [11C]FLB457. The main outcome was D2-R binding potential (BPND) in thalamus, and it was predicted that patients would have lower binding. Diffusion tensor imaging (DTI) was performed in a subgroup of 11 patients and 15 controls. D2-R binding in whole thalamus was lower in patients compared with controls (Cohen’s dz = −0.479, p = 0.026, Bayes Factor (BF) > 4). Among subregions, lower BPND was observed in the ROI representing thalamic connectivity to the frontal cortex (Cohen’s dz = −0.527, p = 0.017, BF > 6). A meta-analysis, including the sample of this study, confirmed significantly lower thalamic D2-R availability in patients. Exploratory analyses suggested that patients had lower fractional anisotropy values compared with controls (Cohen’s d = −0.692, p = 0.036) in the inferior thalamic radiation. The findings support the hypothesis of a dysregulation of thalamic dopaminergic neurotransmission in schizophrenia, and it is hypothesized that this could underlie a disturbance of thalamocortical connectivity.

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RITTER, Frauke, and Bernhard STANDL. "Promoting Student Competencies in Informatics Education by Combining Semantic Waves and Algorithmic Thinkingv." Informatics in Education, April 24, 2022. http://dx.doi.org/10.15388/infedu.2023.07.

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We live in a digital age, not least accelerated by the COVID-19 pandemic. It is all the more important in our society that students learn and master the key competence of algorithmic thinking to understand the informatics concepts behind every digital phenomena and thus is able to actively shape the future. For this to be successful, concepts must be identified that can convey this key competence to all students in such a way that algorithmic thinking is integrated in the subject of informatics - beyond a pure programming course. Furthermore, based on the Legitimation Code Theory, semantic waves provide a way to develop and review lesson plans. Therefore, we planned a workshop, that follow the phases of a semantic wave addressing algorithmic problems using a blockbased programming language. Considering this, we suggest the so-called SWAT concept (Semantic Wave Algorithmic Thinking concept), which is carried out and analyzed in a workshop with students. The workshop was carried out in online format in an 8th grade of a high school during a coronavirus lockdown. The level of algorithmic thinking was measured using a pretest and posttest both in the treatment group and in a control group and with the help of the approximate adjusted fractional Bayes factors for testing informative hypotheses statistically and through a reductive, qualitative content analysis of the students’ work results (worksheets and created programs) evaluated. The semantic wave concept was measured using several cognitive load ratings of the students during the workshop and also statistically evaluated with the approximate adjusted fractional Bayes factors for testing informative hypotheses, as well as a qualitative content analysis of the worksheets. Results of this pilot study provide first insights, that the SWAT-concept can be used in combination of unplugged and plugged parts.

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Hilger, Kirsten, and Matthew J. Euler. "Intelligence and Visual Mismatch Negativity: Is Pre-Attentive Visual Discrimination Related to General Cognitive Ability?" Journal of Cognitive Neuroscience, November 28, 2022, 1–17. http://dx.doi.org/10.1162/jocn_a_01946.

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Abstract EEG has been used for decades to identify neurocognitive processes related to intelligence. Evidence is accumulating for associations with neural markers of higher-order cognitive processes (e.g., working memory); however, whether associations are specific to complex processes or also relate to earlier processing stages remains unclear. Addressing these issues has implications for improving our understanding of intelligence and its neural correlates. The MMN is an ERP that is elicited when, within a series of frequent standard stimuli, rare deviant stimuli are presented. As stimuli are typically presented outside the focus of attention, the MMN is suggested to capture automatic pre-attentive discrimination processes. However, the MMN and its relation to intelligence has largely only been studied in the auditory domain, thus preventing conclusions about the involvement of automatic discrimination processes in humans' dominant sensory modality—vision. EEG was recorded from 50 healthy participants during a passive visual oddball task that presented simple sequence violations and deviations within a more complex hidden pattern. Signed area amplitudes and fractional area latencies of the visual MMN were calculated with and without Laplacian transformation. Correlations between visual MMN and intelligence (Raven's Advanced Progressive Matrices) were of negligible to small effect sizes, differed critically between measurement approaches, and Bayes Factors provided anecdotal to substantial evidence for the absence of an association. We discuss differences between the auditory and visual MMN, the implications of different measurement approaches, and offer recommendations for further research in this evolving field.

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Nakanishi, N., K. Kaikita, M. Ishii, Y. Oimatsu, T. Mitsuse, and K. Tsujita. "P2563Effects of rivaroxaban on cardiac remodeling after experimental myocardial infarction in mice." European Heart Journal 40, Supplement_1 (October 1, 2019). http://dx.doi.org/10.1093/eurheartj/ehz748.0891.

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Abstract Background Rivaroxaban, a direct activated factor X (FXa) inhibitor, has been established for prevention and treatment of arterial and venous thrombosis. Although FXa plays an important role in thrombosis, FXa also involves in inflammation via the protease-activated receptor (PAR)-1 and PAR-2 pathway. We assessed the hypothesis that rivaroxaban might protect cardiac remodeling after myocardial infarction (MI) in mice. Methods MI was induced in wild-type mice by permanent ligation of the left anterior descending coronary artery. At 1 day after MI, mice were randomly assigned to the rivaroxaban and vehicle groups. In the rivaroxaban group, the mice were provided with regular chow diet including rivaroxaban (2400ppm) after the randomization. We evaluated the cardiac function by echocardiography, expression of mRNA and protein in the infarcted and non-infarcted area 7 days after MI. Furthermore, we measured infarct size, infiltration of inflammatory cells by pathological analysis 7 days after MI. Results The fractional shortening (%FS) and Interventricular Septal thickness in diastole (IVSTd) was significantly improved 7 days after MI in the rivaroxaban group compared with the vehicle group (%FS, p=0.01; IVSTd, p=0.013). As for pathological analysis, rivaroxaban decreased infarct size (p=0.026) and the number of infiltrated macrophages in the non-infarcted area (p=0.011) compared with vehicle. The mRNA expression in tumor necrosis factor (TNF)-α, transforming growth factor (TGF)-β in the infarcted area and atrial natriuretic peptide (ANP) in the non-infarcted area was significantly lower in the rivaroxaban group compared with the vehicle (TNF-α, p=0.015; TGF-β, p=0.019; ANP, p=0.012). PAR-1 and PAR-2 mRNA expression in the infarcted area significantly decreased 7 days after MI in the rivaroxaban group compared with the vehicle (PAR-1, p=0.005; PAR-2, p=0.037). Furthermore, western blot analysis demonstrated that the phosphorylation of Extracellular Signal-regulated Kinase (ERK) and c-Jun N-terminal Kinase (JNK) in the non-infarcted area significantly decreased 7 days after MI in the rivaroxaban group compared with the vehicle (ERK, p=0.015; JNK, p=0.002). Conclusions The present study showed that rivaroxaban protected against cardiac dysfunction, probably due to the suppression of PAR-mediated increase of pro-inflammatory cytokines post-MI. Rivaroxaban might be potentially effective for improving the cardiac remodeling after MI. Acknowledgement/Funding This study was supported in part by trust-research grant from Bayer Yakuhin, Ltd.

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Journal articles on the topic 'Fractional Bayes factor'

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